Using Gaussian Process Regression (GPR) models with the Matérn covariance function to predict the dynamic viscosity and torque of SiO2/Ethylene glycol nanofluid …
X Dai, HT Andani, A Alizadeh, AM Abed… - … Applications of Artificial …, 2023 - Elsevier
Studying the dynamic viscosity (DV) is a key factor to determine the nanofluids'
hydrodynamic behavior (NFs). In this research, the effect of volume fraction (φ), shear rate …
hydrodynamic behavior (NFs). In this research, the effect of volume fraction (φ), shear rate …
Using different machine learning algorithms to predict the rheological behavior of oil SAE40-based nano-lubricant in the presence of MWCNT and MgO nanoparticles
M Baghoolizadeh, N Nasajpour-Esfahani… - Tribology …, 2023 - Elsevier
In the present study, using 15 machine learning algorithms (MLP, SVM, RBF, ELM, ANFIS, D-
Tree, MLR, MPR, BPNN, BN, LM, GD, BFGS, XGB and GMDH), the rheological behavior of …
Tree, MLR, MPR, BPNN, BN, LM, GD, BFGS, XGB and GMDH), the rheological behavior of …
Multi-objective optimization of rheological behavior of nanofluids containing CuO nanoparticles by NSGA II, MOPSO, and MOGWO evolutionary algorithms and Group …
R Rostamzadeh-Renani, DJ Jasim… - Materials Today …, 2024 - Elsevier
In this article, the ability of GMDH artificial neural networks (ANNs) to predict the rheological
behavior (RB) of nanofluids (NFs) containing CuO NPs is studied. ANNs are a powerful …
behavior (RB) of nanofluids (NFs) containing CuO NPs is studied. ANNs are a powerful …
Introducing an integrated self-organizing map and radial basis function network for accurate prediction of water-Fe3O4 nanofluid viscosity versus solid volume fraction …
L Chang, W Yang, MK Khabaz, SA Eftekhari… - … and Sustainable Energy …, 2025 - Elsevier
Nanofluids, colloidal suspensions of nanoparticles in base fluids, promise improved thermal
conductivity and energy efficiency. Predicting nanofluid viscosity, influenced by factors like …
conductivity and energy efficiency. Predicting nanofluid viscosity, influenced by factors like …
Thermal conductivity prediction of WO3-CuO-Ag (35: 40: 25)/water hybrid ternary nanofluid with Artificial Neural Network and back-propagation algorithm
One way to enhance the thermal conduction process in heating systems is to attach
substances with high thermal conductivity (TC) to the base fluids. The interesting properties …
substances with high thermal conductivity (TC) to the base fluids. The interesting properties …
Obtaining an accurate prediction model for viscosity of a new nano-lubricant containing multi-walled carbon nanotube-titanium dioxide nanoparticles with oil SAE50
This study aims to investigate the viscosity behavior of multi-walled carbon nanotube
(MWCNT)-titanium dioxide (TiO 2)(40− 60)-SAE50 oil nanofluid using an Artificial Neural …
(MWCNT)-titanium dioxide (TiO 2)(40− 60)-SAE50 oil nanofluid using an Artificial Neural …
Dynamic viscosity prediction using artificial intelligence for an antifreeze containing MWCNT–alumina hybrid nanopowders
This paper investigates the impact of Solid Volume Fraction (SVF) and temperature on the
dynamic viscosity of a hybrid antifreeze composed of MWCNTs and aluminum oxide in a …
dynamic viscosity of a hybrid antifreeze composed of MWCNTs and aluminum oxide in a …
Artificial neural network modeling of thermal characteristics of WO3-CuO (50: 50)/water hybrid nanofluid with a back-propagation algorithm
Thermophysical properties such as thermal conductivity (k nf) make the use of fluid suitable
for heat transfer. Fluids such as water have limited applications due to their low thermal …
for heat transfer. Fluids such as water have limited applications due to their low thermal …
[HTML][HTML] On the thermal performance of nanofluid over a cylinder within a confined channel: The splitter effect
SAR Sahebi, DD Ganji, J Alinezhad - Case Studies in Thermal Engineering, 2023 - Elsevier
Implementing splitters in microchannels enhances fluid distribution, and nanofluids offer a
promising approach to improving heat transfer efficiency. This study uses a home-written …
promising approach to improving heat transfer efficiency. This study uses a home-written …
[HTML][HTML] Numerical investigation of rigidity and flexibility parameters effect on superstructure foundation behavior using three-dimensional finite element method
A comprehensive three-dimensional finite element of the superstructure foundation model
includes the effect of lots of important parameters on the structure performance. Among …
includes the effect of lots of important parameters on the structure performance. Among …